The e‐tongue‐based classification and authentication of mineral water samples using cross‐correlation‐based PCA and Sammon's nonlinear mapping

The present paper elaborates on the design of classifiers based on cross‐correlation‐based principal component analysis (PCA) and Sammon's nonlinear mapping (NLM) using current signals obtained from electronic tongue (e‐tongue) with commercial mineral water samples available in the Indian market. The pulse‐voltammetric method is used to capture the electroanalytical/electrochemical characteristics of the sampled mineral waters by considering a real model for the liquid–electrode interface in a given e‐tongue apparatus. Then the cross‐correlation coefficients between the output and input signals are determined. Both PCA and Sammon's NLM create a subspace from high‐dimensional mineral water data by considering the principal eigenvectors and minimising the stress function, respectively. The proposed cross‐correlation‐based PCA and Sammon's classifiers establish the highest separation distance among the investigated water brands and carries out the authentication of more than one unknown sample of the same brand with a certain degree of variability with respect to their sources. Copyright © 2013 John Wiley & Sons, Ltd.